Cooperative spectrum sensing against noise uncertainty using Neyman-Pearson lemma on fuzzy hypothesis test

  • Authors:

  • Abdolreza Mohammadi;Mohammad Reza Taban;Jamshid Abouei;Hamzeh Torabi

  • Affiliations:

  • Department of Electrical and Computer Engineering, Yazd University, 89195-741, Yazd, Iran;Department of Electrical and Computer Engineering, Yazd University, 89195-741, Yazd, Iran;Department of Electrical and Computer Engineering, Yazd University, 89195-741, Yazd, Iran;Department of Mathematics, Yazd University, 89195-741, Yazd, Iran

  • Venue:
  • Applied Soft Computing
  • Year:
  • 2013

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Abstract

In this paper, we consider the problem of cooperative spectrum sensing in the presence of the noise power uncertainty. We propose a new spectrum sensing method based on the fuzzy hypothesis test (FHT) that utilizes membership functions as hypotheses for the modeling and analyzing such uncertainty. In particular, we apply the Neyman-Pearson lemma on the FHT and propose a threshold-based local detector at each secondary user (SU) in which the threshold depends on the noise power uncertainty. In the proposed scheme, a centralized manner in the cooperative spectrum sensing is deployed in which each SU sends its one bit decision to a fusion center. The fusion center makes a final decision about the absence/presence of a primary user (PU). The performance of the PU's signal detection is evaluated by the probability of signal detection for a specific signal to noise ratio when the probability of false alarm is set to a fixed value. The performance of the proposed algorithm is compared numerically with two classical threshold-based energy detectors. Simulation results show that the proposed algorithm considerably outperforms the methods with a bi-thresholds energy detector and a simple energy detector in the presence of the noise power uncertainty.